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Abstract

Background

There are striking similarities between the innate immune systems of invertebrates
and vertebrates. Caenorhabditis elegans is increasingly used as a model for the study of innate immunity. Evidence is accumulating
that C. elegans mounts distinct responses to different pathogens, but the true extent of this specificity
is unclear. Here, we employ direct comparative genomic analyses to explore the nature
of the host immune response.

Results

Using whole-genome microarrays representing 20,334 genes, we analyzed the transcriptional
response of C. elegans to four bacterial pathogens. Different bacteria provoke pathogen-specific signatures
within the host, involving differential regulation of 3.5-5% of all genes. These include
genes that encode potential pathogen-recognition and antimicrobial proteins. Additionally,
variance analysis revealed a robust signature shared by the pathogens, involving 22
genes associated with proteolysis, cell death and stress responses. The expression
of these genes, including those that mediate necrosis, is similarly altered following
infection with three bacterial pathogens. We show that necrosis aggravates pathogenesis
and accelerates the death of the host.

Conclusion

Our results suggest that in C. elegans, different infections trigger both specific responses and responses shared by several
pathogens, involving immune defense genes. The response shared by pathogens involves
necrotic cell death, which has been associated with infection in humans. Our results
are the first indication that necrosis is important for disease susceptibility in
C. elegans. This opens the way for detailed study of the means by which certain bacteria exploit
conserved elements of host cell-death machinery to increase their effective virulence.

Background

Mammals defend themselves from infection via two inter-dependent types of immunity:
innate and adaptive. Innate immune mechanisms represent front-line protection against
pathogens and instruct the subsequent adaptive response. One of the principal attributes
of the adaptive immune system is its remarkable specificity, based on somatic gene
rearrangement and hypermutation leading to an extremely large repertoire of T- and
B-cell receptors and antibodies. While such adaptive immunity is restricted to jawed
vertebrates, invertebrates rely on their innate immune defenses. Until recently, these
were generally considered to be relatively non-specific. For example, insects were
known to mount distinct responses to different broad classes of pathogens (fungi,
Gram-negative and Gram-positive bacteria) but assumed not to have pathogen-specific
defense mechanisms [1]. There is, however, increasing evidence to suggest that the innate immune system
may confer specific protection to the host even in invertebrates. For example, in
insects, alternative splicing gives rise to thousands of distinct isoforms of the
Dscam protein, a homolog of the human DSCAM (Down syndrome cell adhesion molecule)
that has been proposed to be involved in pathogen recognition [2]. Different pathogens appear to stimulate the production of different subsets of Dscam
isoforms and there is even the suggestion from studies with mosquitoes that isoforms
preferentially bind the pathogen that induces their production [3]. Very recently, it has been shown that inoculation of Drosophila melanogaster with Streptococcus pneumoniae specifically protects against a subsequent challenge with this pathogen, but not against
other bacterial species [4].

Nematode worms, such as Caenorhabditis elegans, are exposed to many pathogens in their natural environment and are expected to have
evolved efficient defense mechanisms to fight infection. In the laboratory, C. elegans is cultured on an essentially non-pathogenic strain of Escherichia coli. This can easily be substituted with a pathogenic bacterium, readily allowing analysis
of bacterial virulence mechanisms and host defenses. C. elegans has been used for the past few years as a model host for the study of the molecular
basis of innate defenses, but compared to D. melanogaster, these studies are still very much in their infancy [5,6]. Nevertheless, using genetically diverse natural isolates of C. elegans and the bacterial pathogen Serratia marcescens, it has been shown that there is significant variation in host susceptibility and
significant strain- and genotype-specific interactions between the two species [7]. Additionally, the transcriptional response of C. elegans to a number of different bacterial pathogens has been determined [8-11]. Given the relatively small overlap between the sets of genes identified as being
transcriptionally regulated following infection with different pathogens, the combined
results suggest a substantial degree of specificity in the innate immune response
of C. elegans. One important caveat, however, is that these results were obtained in different
laboratories using different microarray platforms. Indeed, as discussed further below,
a comparison of two different studies both using Pseudomonas aeruginosa [10,11] revealed substantial differences in the apparent host response. This may reflect
the known limitations of microarrays that have been well documented [12,13].

To investigate the specificity of the transcriptional response of C. elegans to infection, we have carried out a comparative microarray study at a fixed time-point
using one Gram-positive and three Gram-negative bacterial pathogens. Their pathogenicity
against C. elegans has been characterized previously [14-16]. Our analyses suggest that distinct pathogens provoke unique transcriptional signatures
in the host, while at the same time they revealed a common, pathogen-shared response
to infection. One prominent group of genes found within the pathogen-shared response
was aspartyl proteases. These have diverse biological roles, including an important
function in necrosis [17]. Consistent with this, we observed that bacterial infection was indeed associated
with extensive necrotic cell death in the nematode intestine. Furthermore, using fluorescent
reporter genes, we confirmed that aspartyl proteases implicated in necrosis are up-regulated
during infection. In contrast to programmed cell death or apoptosis, necrosis is induced
by environmental insults [18]. In many species, apoptosis serves a protective function, limiting pathogen proliferation
[19]. Post-embryonic apoptosis in C. elegans occurs only in the somatic cells of larvae during early development, prior to the
third larval (L3) stage, and in the germline of adult animals [20]. Germline apoptosis has been shown to mediate an increased resistance to Salmonella infection in C. elegans [21]. To address the question of whether necrosis observed in the adult soma during infection
has a protective role, we analyzed the survival of necrosis-deficient mutants. We
found that these animals were significantly more resistant to infection than wild-type
worms, suggesting that necrosis is an integral and deleterious part of the infection-induced
pathology. Since bacteria exploit conserved elements of the host's cell death machinery
to increase their effective virulence, these results may provide insights into host-pathogen
interactions in higher species.

Results

Exploratory analyses of host response to infection

To determine the degree of specificity in the response of C. elegans to bacterial infection, we carried out a whole-genome, comparative analysis of worms
infected with one Gram-positive and three Gram-negative bacterial pathogens using
long-oligo microarrays. We first looked at the response to S. marcescens and found less than a 2% overlap between the genes identified as being up-regulated
by S. marcescens in this study (supplementary Table 1a in Additional data file 3) and a previous investigation,
which employed a different microarray platform based on nylon cDNA filters with partial
genome coverage [8]. This underlines the difficulty in making direct comparisons between studies employing
different experimental designs.

Studies with C. elegans generally use worms cultured on the standard nematode growth medium (NGM) agar. On
the other hand, the Gram-positive bacterium Enterococcus faecalis is most pathogenic when cultured on a rich medium (brain heart infusion (BHI) agar)
[15]. To eliminate possible effects of the medium on nematode physiology, we wished to
carry out all infections on worms grown on NGM agar. We determined that E. faecalis was still pathogenic to C. elegans when grown on NGM agar, if pre-cultured in liquid BHI medium (supplementary Figure
1 in Additional data file 1), and adopted this protocol for our analyses.

Figure 1. Comparison of host gene expression profiles following infection with different pathogens.
Expression levels are indicated by a color scale and represent normalized differences
between infected and control animals. Grey denotes genes not considered to be differentially
regulated under that condition. The numbers on the vertical axis correspond to differentially
regulated genes. Each column shows the expression levels of individual genes (represented
as rows) following infection by the pathogens as indicated on the horizontal axis
(S. m, S. marcescens; E. f, E. faecalis; E. c, E. carotovora; P. l, P. luminescens). (a) Genes differentially regulated in an infection with P. luminescens and their comparative expression levels with other pathogens. (b) Genes defining a pathogen-specific signature specifically up-regulated with P. luminescens infection. (c) Groupings, as indicated by the horizontal bars, formed after clustering using non-redundant
sets of genes that were up- and down-regulated by at least two pathogens (trees not
shown). (d) Genes commonly up-regulated following E. carotovora, E. faecalis and P. luminescens infections.

Comparing the levels of expression for genes that were up- or down-regulated at a
single time point by each individual bacterial pathogen (S. marcescens; E. faecalis; Erwinia carotovora; Photorhabdus luminescens), we observed expression profiles that were characteristically unique, or 'pathogen-specific
signatures'. For example, the majority of genes with expression levels altered in
one direction following infection by P. luminescens were either unchanged or responded differently in infections with other pathogens
(Figure 1a,b; supplementary Table 1a,b in Additional data file 3). Thus, 24 h post-infection,
C. elegans is clearly capable of mounting a response that is principally different for each of
the pathogens used in this study. From non-redundant groups of 2,171 genes up-regulated
and 2,025 genes down-regulated after infection with at least one pathogen, only 254
and 266 genes, respectively, were identified to be commonly regulated by more than
one pathogen (supplementary Table 1c in Additional data file 3). These comparatively
small numbers reinforce the notion of pathogen-specific responses, while at the same
time suggesting that host responses to different pathogens have common facets. To
examine this further, we performed clustering analyses with both the commonly up-
and down-regulated genes. In both cases, groupings composed of genes responding similarly
to different pathogens were observed (Figure 1c). Surprisingly, the response to the Gram-positive bacterium, E. faecalis, overlapped to a greater extent with those provoked by the Gram-negative bacteria
P. luminescens and E. carotovora than did the response provoked by a third Gram-negative bacterium, S. marcescens. Thus, for example, one grouping was identified for genes with altered expression
following infection with the first three bacteria, to the exclusion of S. marcescens (Figure 1d). Overall, highest similarity existed between the genes whose expression was altered
following infection with E. carotovora and P. luminescens.

The large numbers of genes identified as being transcriptionally regulated upon infection
represents a challenge for meaningful interpretation. In our study this problem was
further compounded by the inclusion of multiple pathogens, which as a consequence,
required the analysis of diverse datasets. The use of Gene Class Testing [22] to identify functional associations can, however, help in the identification of biologically
relevant themes. We therefore used the freely available Expression Analysis Systematic
Explorer (EASE) [23] to identify gene classes significantly over-represented among genes regulated as
a consequence of infection. In our analyses, we looked at gene classes derived using
Gene Ontology, euKaryotic Orthologous Groups and functional information from published
experiments using C. elegans (see Materials and methods). Biological themes were formed via the grouping of gene
classes in an ad hoc fashion, with all members of a group having similar biological functions. For example,
the 'infection-related response' class includes genes described in published studies
as being up- or down-regulated by infection, together with any structurally homologous
genes.

With EASE we identified two major groupings of gene classes. The first, termed 'pathogen-shared',
is composed of gene classes identified across infections with different pathogens
(Figure 2a; supplementary Table 2a in Additional data file 3). These include classes shared
by genes with similar expression profiles in E. faecalis, E. carotovora and P. luminescens infections and that can be further associated with proteolysis, cell death, insulin
signaling and stress responses. Other gene classes shared by E. faecalis and P. luminescens include lysozymes, genes expressed in the intestine and genes implicated in the response
to infection with Microbacterium nematophilum, a Gram-positive nematode-specific pathogen [9]. There was similarly an over-representation of genes up-regulated following infections
with E. carotovora and P. luminescens that are associated with infection by another Gram-negative pathogen, P. aeruginosa [11]. A second grouping defined the 'pathogen-specific' responses (Figure 2b; supplementary Table 2b in Additional data file 3). For example, only E. faecalis infection was associated with a significant down-regulation of hormone receptors,
while P. luminescens infection involved a significant elevation of the proportion of genes described to
be under the control of p38 MAPK and TGF-β signaling pathways [10,24]. Biological themes associated with host response to adverse conditions, including
infection, can be found within both the pathogen-specific and pathogen-shared groupings
(Figure 2). Thus, as further discussed below, clustering analysis of gene expression and gene
class testing are both consistent with the notion that the response of C. elegans to infection can be defined by two biologically relevant signatures, one being pathogen-shared
and the other, pathogen-specific.

Statistical testing of gene expression

While fold change measurements are conceptually useful when performing exploratory
analyses, they lack known and controllable long-range error rates [22]. We therefore performed complementary analyses in which exploratory findings using
fold change-derived data were combined with results obtained using two established
statistical tools, MAANOVA and BRB-ArrayTools (see Materials and methods). With the
two exploratory analyses, a grouping of host-responses observed following infection
with E. carotovora, E. faecalis and P. luminescens was the most consistent (Figures 1c and 2a). We therefore used MAANOVA and BRB-ArrayTools on microarray data obtained with these
three pathogens to investigate further the nature of this apparent pathogen-shared
host-response. We identified a total of 22 high-confidence genes with significant
differences in expression between control animals and animals infected with the three
pathogens (Table 1; supplementary Table 3a in Additional data file 3). Prominent among these 'common
response genes' is lys-1, which was one of the first infection-inducible genes to be identified in C. elegans [8]. Following the demonstration that it was up-regulated by S. marcescens infection, lys-1 has also been shown to be part of the response of the worm to P. aeruginosa [11]. The list also includes a gene that encodes a lipase, a class of protein important
in the response to S. marcescens [8] and M. nematophilum [9], as well as a saposin-encoding gene. All the corresponding proteins are expected
to have antimicrobial activity and, therefore, to contribute directly to defense [25,26]. Other genes correspond to a C-type lectin (clec-63), a putative LPS-binding protein (F44A2.3), and proteins containing Complement Uegf Bmp1 (CUB) and von Willebrand Factor (vWF)
domains and vWF, epidermal growth factor (EGF) and lectin domains, respectively; all
of these could be involved in pathogen recognition [25,26]. Members of the largest class of genes, however, encode aspartyl proteases not previously
associated with the response to infection in C. elegans.

Neither up- nor down-regulated genes exhibited any substantial genomic clustering
of the type described for genes involved in the response to M. nematophilum infection [9]. With regards to down-regulated genes within the pathogen-shared response identified
in this study, they are all seemingly metabolism-related; a similar phenomenon has
been previously described in worms infected with M. nematophilum [9].

Validation of common response genes by quantitative real-time PCR

To validate these results, we examined in more detail the regulation of three asp genes encoding aspartyl proteases, as well as a C-lectin, encoded by clec-63, using quantitative real time-PCR (qRT-PCR). Since only a small number of common
response genes was identified during statistical testing, we also looked at the expression
of two other clec genes, one being clec-65, the genomic neighbor of clec-63, and the other clec-67, reported to be induced by M. nematophilum [9]. At 24 h, all six genes showed a marked up-regulation following infection by E. faecalis, E. carotovora and P. luminescens, whereas they did not show a substantial change in expression following S. marcescens infection (Figure 3a). We hypothesized that this result could be a consequence of the different pathogenicities
of the bacteria. To investigate this, we carried out a time course study over a period
of five days, using qRT-PCR to follow relative expression levels of asp-3, asp-6 and clec-63 in worms infected by S. marcescens. The expression levels of these three genes indeed increased over this period (Figure
3b), suggesting that their induction is linked to pathogenesis more than to pathogen
recognition.

Figure 3. qRT-PCR analyses. (a) Expression levels of common response genes representing two gene families were measured
and data reported as mean difference between infected and control animals following
infection with the four pathogens (S. m, S. marcescens; E. f, E. faecalis; E. c, E. carotovora; P. l, P. luminescens). (b) The expression levels of asp-3, asp-6 and clec-63 were followed over a period of five days in C. elegans infected with S. marcescens; data reported as mean difference between infected and control animals. Bars represent
standard errors (at least two independent measurements). (c) The antimicrobial gene nlp-29 responds specifically to fungal infection. The expression levels of nlp-29 were measured following infection with the fungal pathogen (D. c, D. coniospora) and the four bacterial pathogens. Data are reported as mean difference between infected
and control animals. Bars represent standard errors (three independent measurements).

Common response gene transcription is not altered by fungal infection

In contrast to the bacterial pathogens used in this study that infect C. elegans via the intestine, the fungus Drechmeria coniospora infects nematodes via the cuticle [27]. A comparison of the common response genes with those having an altered expression
following infection with D. coniospora, determined under similar experimental conditions to those used in this study (Pujol
et al., submitted), showed absolutely no overlap (results not shown). This clear distinction
between bacterial and fungal infection was unexpected since we had previously reported,
based on our results using cDNA microarrays, that the antimicrobial peptide gene nlp-29 was induced upon infection both by S. marcescens and D. coniospora [27]. This gene appeared not to be up-regulated, however, by any of the bacterial pathogens
used in this study, including S. marcescens. When we assayed the level of nlp-29 expression in worms infected by the different pathogens using qRT-PCR, we found that
only D. coniospora induced a substantial increase (Figure 3c). We recently found that nlp-29 is induced under conditions of high osmolarity (Pujol et al., submitted), including when plates used for culturing worms become drier after a
few days storage. The age of plates was not a variable that was previously controlled,
and we now believe this to be the most likely reason for having erroneously identified
nlp-29 as a gene induced by S. marcescens infection. These results underline the fact that C. elegans mounts distinct responses to bacterial and fungal infection.

Expression domains of common response genes

The response of C. elegans to infection by S. marcescens and P. aeruginosa involves predominantly genes expressed in the intestine [8,11]. Information regarding the expression patterns for 19 of the 22 common response genes
differentially regulated after infections with E. faecalis, E. carotovora and P. luminescens is available (supplementary Table 3a in Additional data file 3). Of these, 16 are
expressed in the intestine of the adult animal. Examination of their proximal promoter
regions using BioProspector [28] revealed GATA motifs in 43% of these genes (supplementary Table 3a in Additional
data file 3), consistent with similar findings from a recent study [11]. Two other genes, npp-13 and K06G5.1, are known to be expressed in the gonad. By in situ hybridization, the remaining gene, F44A2.3, is reported to show weak but specific expression at the vulva and in the head. This
gene also attracted our attention as it encodes a protein containing a lipopolysaccharide-binding
protein (LBP)/bactericidal permeability-increasing protein (BPI)/cholesteryl ester
transfer protein carboxy-terminal domain (Pfam accession number PF02886), associated
with bacterial recognition or killing in many species [29,30]. We determined its expression pattern by generating transgenic strains carrying green
fluorescence protein (GFP) under the control of the F44A2.3 promoter. We observed high levels of constitutive GFP expression in the pre-anal,
vulval, hypodermal, glial amphid socket and excretory duct cells of the adult animal
(Figure 4a-i). Upon infection of worms carrying the reporter gene with E. carotovora or P. luminescens, there was no perceptible change in the level of GFP expression at 24, 48 or 72 h
post-infection (results not shown). Similarly, these two pathogens caused no discernable
induction of GFP expression at any time up till 72 h post-infection in strains carrying
5 other transcriptional reporter genes (asp-5 and -6, clec-63, -65 and -67; results not shown). Thus, based on the genes tested, we were unable to identify
robust in vivo reporters for the response to bacterial infection. The cells that expressed pF44A2.3::GFP are in privileged sites, in contact with the external environment, hinting at
a potential front-line role for F44A2.3 in pathogen recognition. We addressed any potential role in resistance to infection
by inactivating its expression by RNAi, but did not see any significant effect on
survival (supplementary Figure 2 in Additional data file 1).

Figure 4. Expression domains of common response genes and symptoms associated with infection.
pF44A2.3::GFP expression in the (a) ventral nerve-cord, (b) hypodermis, (c-d) P12.pa pre-anal cells, (e-f) glial amphid socket cells, (g-h) excretory duct cell and (i) vulE or uv1 cells. Red fluorescence comes from the pcol-12::dsRED co-injection marker. In areas where both GFP and dsRED are expressed, yellow is observed.
(j,k) Vacuoles (arrows) can be observed within intestinal cells of P. luminescens-infected adults (j), in which there is detectable expression of asp-4::GFP (k). Similar results were obtained with infected adults expressing asp-3::GFP. In contrast, no GFP expression or vacuolization was seen in the intestines
of non-infected worms.

Necrosis aggravates infection-associated pathology

In contrast to the reporter genes listed above, we observed a clear and reproducible
induction of expression of the asp-3 and -4 reporter genes. In the absence of infection, virtually no GFP was detectable, while
after exposure to E. carotovora or P. luminescens there was an accumulation of GFP within large vacuoles formed in the intestine (Figure
4j-k). We observed a qualitatively similar induction of reporter gene expression following
infection with E. faecalis but of a lower magnitude (results not shown).

When the asp-4::GFP reporter was transferred by mating into pmk-1(km25) or dbl-1(nk3) mutant backgrounds, we observed an induction of GFP expression following infection
with E. carotovora that was similar to that seen in wild-type worms (results not shown). The two mutants
respectively affect the p38 MAPK and TGF-β pathways, important for resistance to bacterial
infection. Thus, these results suggest that infection-induced expression of ASP-4
is independent of the two pathways.

Both asp-3 and -4 have been specifically associated with the execution of necrotic cell death in C. elegans [17]. Indeed, inspection of worms during infection revealed the frequent incidence of
necrotic cell death in the intestine, which is manifested by the vacuole-like appearance
of cells (Figure 4j), not seen within the intestine of healthy animals. These dramatically swollen cells
have distorted nuclei restricted in the periphery, a most prominent characteristic
of necrotic cell death. Preliminary observations suggested that infection under different
culture temperatures (25°C and 20°C) progresses similarly in terms of symptoms and
asp::GFP reporter gene expression, except that at 25°C everything was more rapid. In
subsequent experiments, we therefore conducted infections at 20°C to increase the
temporal resolution. The appearance of necrosis follows the spatiotemporal progression
of infection. The first tissue affected is the intestine, where vacuolated cells were
observed around 24 h post-infection. After the second day of infection, the epidermis
and the gonad become severely distorted and displayed similar necrotic vacuoles. This
pattern of necrotic death, observed following infection with different pathogens,
could be part of an inducible defense mechanism contributing to host survival, or
a deleterious consequence of infection. To differentiate between these two possibilities,
we assayed the resistance to infection of two necrosis-deficient C. elegans mutants, vha-12(n2915) and unc-32(e189), that both affect V-ATPase activity [31,32]. The two mutants showed enhanced survival, relative to wild-type N2 worms in infections
with E. carotovora (Figure 5a) and P. luminescens (Figure 5b). Given that these mutants display abnormal pharyngeal pumping, we were concerned
that resistance might be the consequence of a reduced bacterial load. We therefore
directly assayed the number of viable bacteria within worm intestines at 24 h post-infection.
With E. carotovora, there was no difference between infected wild-type and mutant animals (Figure 5c), while for P. luminescens, unc-32 animals had a higher bacterial load (Figure 5d). Therefore, differences in bacterial accumulation are not correlated with resistance
of the two mutants to infection. Certain mutants of the insulin/insulin growth factor
signaling pathway, such as daf-2, exhibit increased pathogen resistance and longevity [33]. To examine whether vha-12 and unc-32 are more infection-resistant due to general effects in survival and ageing, we measured
the longevity of these mutants on non-pathogenic E. coli and found that they had similar lifespans to wild-type animals (Figure 5e), consistent with previous findings [34]. We also observed that the induction of asp-4::GFP by E. carotovora and P. luminescens was unchanged in a vha-12 mutant background (supplementary Figure 3 in Additional data file 1). Thus, mutants that have a defect in intracellular organelle
acidification are necrosis-deficient and exhibit a specific increase in their resistance
to infection that appears to be independent of asp-4 activity.

Figure 5. Suppression of necrosis increases resistance of worms to infection. Both vha-12(n2915) and unc-32(e189) are associated with a defect in vacuolar H+-ATPase activity and, consequently, reduced necrosis. Following infection with (a) E. carotovora and E. carotovora (b) E. carotovora, the differences between wild-type N2 and vha-12(n2915) or unc-32(e189) survival are highly significant (log-rank test, p value < 0.0001). Data shown are representative of three independent experiments. (c,d) Bacterial load in the intestines of wild-type and mutant C. elegans (indicated on the horizontal axes), after 24 h exposure to E. carotovora (c) and P. luminescens (d). The number of colony-forming units (CFU) per worm was measured and bars represent
the standard errors from two independent experiments. (e) Life-span assays for the mutants vha-12(n2915) and unc-32(e189) and wild-type N2 on non-pathogenic OP50 E. coli. Differences between the three strains are not significant (log-rank test, p value > 0.05).

Discussion

In vertebrates, in addition to the highly specialized and specific mechanisms of the
adaptive immune system, a first line of defense constituted by the innate immune system
involves the recognition of different classes of pathogens via germline-encoded proteins
such as the Toll-like receptors [35]. The degree to which invertebrates are also able to respond specifically to infection
is a question of considerable interest [36]. In this study we investigated whether infection of C. elegans by taxonomically distinct bacterial pathogens provokes distinct changes in gene expression.
A principal motivation for the study was the difficulty in drawing conclusions from
comparisons between studies using different experimental designs. For example, of
a total of 392 genes reported to be induced in worms infected with P. aeruginosa in two independent studies, less than 20% were found in both [10,11]. With regards to our own results, there was essentially no overlap between the genes
or gene classes found to be up-regulated by S. marcescens in this and a previous study [8].

Through the use of exploratory analyses, we identified genes that are regulated differentially
by the pathogens used in this study. Employing three biologically replicated datasets
from synchronized populations at a single time-point and the computational methods
described, a robust statistical significance could not be ascribed to changes in individual
gene expression associated with the pathogen-specific responses. This is probably
because the datasets for individual pathogens were relatively small and contained
inherent experimental variation. Nevertheless, a strong trend emerged from the groups
of non-overlapping genes that define these responses, and when combined with results
from previous studies [8-11] strongly suggest that C. elegans is capable of mounting a distinct response to different bacterial pathogens.

In contrast to the above, with the use of these same statistical tools we were able
to define a group of common response genes having similar expression profiles across
infections with three different pathogens (Table 1). We consider this high-confidence group to be a minimum set, since it is possible
that a more extensive study employing more replication in the experimental design,
different time-points or changed for other parameters would reveal additional genes
to be commonly regulated by multiple pathogens. Pathogens that vary considerably in
their virulence and that provoke different symptoms were used. Therefore, in the context
of this study, common response genes are potentially constituents of mechanisms underlying
a pathogen-shared, host-response to different infections. Many of these genes have
been functionally characterized as participating in the response of C. elegans to various forms of stress as well as to infection by bacterial pathogens. Specific
examples include lys-1 and clec-63, a lysozyme and C-type lectin, respectively. Both the lysozyme and C-type lectin
classes of genes are known to have roles in innate immunity [8,9]. The expression of lys-1 is also modulated by insulin signaling [37] and by a toxin-induced stress response [38]. Taken as a whole, this suggests that common response genes may be regulated not
only as a direct result of infection, but also by other factors consequent upon infection.

On the other hand, common response genes are not induced by infection with the fungus
D. coniospora. Indeed, the signature of gene transcription associated with fungal infection is
completely different from that provoked by the four bacterial pathogens used in this
study. As discussed above, the antimicrobial peptide gene, nlp-29 is induced only by D. coniospora. We had previously reported that a second antimicrobial peptide gene, cnc-2, was induced upon infection both by S. marcescens and D. coniospora, based on our results using cDNA microarrays [27]. cnc-2 was found to be up-regulated by P. aeruginosa infection [10] and suggested to be a 'general response gene'. Like nlp-29, cnc-2 appeared not to be up-regulated by any of the bacterial pathogens used in this study,
nor in our hands by P. aeruginosa (CL Kurz, personal communication). Nor was cnc-2 induced by high osmolarity (OZugasti, personal communication). On the other hand,
the structurally related gene cnc-7 is up-regulated under conditions of osmotic stress (T Lamitina, personal communication).
The cDNA microarrays we used previously do not have a cnc-7-specific probe, but the sequence of the cnc-7 mRNA is >80% identical to that of cnc-2. Therefore, it is possible that dry plate conditions induced cnc-7 expression and cross-hybridization resulted in the erroneous detection of increased
cnc-2 transcript levels.

As mentioned previously, the down-regulated common response genes identified in this
study appear to have functions associated with general metabolism. For example, the
genes that show the greatest down-regulation, acdh-1 and -2, encode acyl-CoA dehydrogenases involved in mitochondrial β-oxidation and the metabolism
of glucose and fat. Their expression levels are also repressed upon starvation [39,40]. The modulation of their expression by pathogens could reflect a reduction in food
uptake upon infection, or be part of a mechanism to control cellular resources and
limit their availability to pathogens. The role that transcriptional repression plays
in the innate immune response of C. elegans must be the subject of future studies.

Common response genes identified in this study include a grouping of seven genes associated
with proteolysis and cell death, asp-1, 3, 4, 5 and 6, T28H10.3 and Y39B6A.24. With the exception of Y39B6A.24, all others are known to be expressed in the intestine (supplementary Table 3b in
Additional data file 3). Using information from the Pfam database [41], all seven have been annotated as possessing a potential amino-terminal signal sequence.
Interestingly, the remaining member of the aspartyl protease-encoding ASP family,
ASP-2, which is not part of the pathogen-shared response, does not possess a comparable
signal-sequence. While some aspartyl proteases within the cathepsin Esub-family are
known to be secreted into the nematode intestine [42], experimental observations with full-length GFP fusions for ASP-3 and -4 indicate
a predominantly lysosomal localization [17]. This suggests that the intracellular targeting of up-regulated proteases to lysosomes
and perhaps other sub-cellular organelles, such as mitochondria, may be crucial for
their proper functioning.

In C. elegans, necrosis is the best characterized type of non-apoptotic cell death [18]. Necrotic cell death is triggered by a variety of both extrinsic and intrinsic insults
and is accompanied by characteristic morphological features. Our findings provide
the first description of pathogen-induced necrosis in this model organism. While necrosis
has been associated with infection in other metazoans, its role during infection remains
unclear. Necrosis has been implicated in defensive or reparative roles following cellular
damage, and necrotic cell death in tissues that have been compromised after vascular-occlusive
injury triggers wound repair responses [43]. Successful pathogens overcome physical, cellular, and molecular barriers to colonize
and acquire nutrients from their hosts [44]. In such interactions, it has been suggested that the cellular machinery of the host
may in fact be exploited by viral and bacterial pathogens that induce necrotic cell
death, resulting in damage to host tissue. For example, during Shigella-mediated infection, necrosis-associated inflammation is induced within intestinal
epithelial cells of the host by the pathogen [45].

Our results suggest that in C. elegans, some experimental bacterial infections provoke a common program of gene regulation
with consequences that include the promotion of necrosis in the intestine. Thus, these
bacteria appear to exploit the necrotic machinery of C. elegans via a common host mechanism. While pathogen-induced necrosis might be protective for
some infections, for the two bacteria tested, it appears to have no protective role
and apparently hastens the demise of the host during the course of infection. Although
there is increasing evidence for co-evolution between C. elegans and S. marcescens [7,46], and E. carotovora, E. faecalis and P. luminescens can be found in the soil [47-49], there is no reason to believe that the bacteria used in this study developed virulence
mechanisms to induce necrosis specifically in C. elegans.

In many cases, groups of genes that function together in the host response to pathogens
or parasites share common regulation [11,50]. We sought to identify other genes that potentially function alongside common response
genes within the intestine, but that were not identified for whatever reason as being
transcriptionally regulated in this study. These include those having the potential
for common transcriptional regulation. Unfortunately, there is still no simple relationship
between transcriptional co-regulation and regulatory motifs [51]. Efforts are being made to this end, however, and data for regulatory motifs in C. elegans are available within the cis-Regulatory Element Database (cisRED) [52]. Relevant information could be obtained for only five common response genes expressed
in the intestine (supplementary Table 4a in Additional data file 3). These are associated
via shared, predicted motif groups with a number of other intestinally expressed genes
(Figure 6; supplementary Table 4b in Additional data file 3). All five common response genes
are associated with biological themes relevant to infection (see Results) and we observed
similar associations with a number of the genes having shared genomic motifs (Figure
6; supplementary Table 4c in Additional data file 3). We postulate that these genes,
associated with common response genes on the dual basis of shared motifs, found within
genomic regions conserved across closely related species, and functional relevance,
may potentially be intestine-localized components of a pathogen-shared response.

Figure 6. Modeling the molecular basis underlying an intestine-localized, pathogen-shared response
to infection in C. elegans. Three major components make up the model; the common response genes identified directly
in this study, genes associated with common response genes on the basis of shared
DNA motifs, and interactors of the common response genes, either genetic (Wormbase)
or physical (core or scaffold; InteractomeDB). Unambiguous evidence for expression
in the intestine exists for all indicated genes. The relevant biological functions
are shown in different colors.

We also took advantage of published interaction data from InteractomeDB [53,54] and WormBase [55], to identify other genes and proteins that could potentially function alongside common
response genes within the intestine. Of all common response genes expressed in the
intestine, relevant interaction networks could be established only for asp-3 and asp-6 (Figure 6; supplementary Table 4d in Additional data file 3). With the exception of the interaction
between ERM-1 and ASP-3 that was identified in a large-scale study, all other interactions
shown have additional evidence obtained via small-scale studies. ERM-1 appears to
be primarily involved in the maintenance of intestinal cell integrity; abrogation
of erm-1 function by RNAi provokes distortion of the intestinal lumen in the adult animal [56]. In the case of itr-1 and crt-1, both have been implicated in the control of necrotic cell death [57] via regulation of intracellular calcium [18]. It follows that in the context of an interaction-network, their association with
the common response gene asp-6 may be an indication of their involvement in intestinal cell necrosis provoked by
infection. Such a possibility awaits experimental verification.

Conclusion

This study has revealed that the infection of C. elegans with different bacterial pathogens can be characterized by a host response that is
both pathogen-specific and pathogen-shared in nature. Unique gene expression profiles,
which define the pathogen-specific responses to infection, are associated with common
biological functions relevant in the context of host innate immunity. Necrosis, induced
by different bacteria in the pathogen-shared response to infection, has a common basis
at the molecular level, appears to have no obvious protective-role and its suppression
increases host resistance. Consequently, targeting molecular components to prevent
necrotic cell death in C. elegans, and possibly other animals, may have important implications for host resistance
to infection mediated by multiple pathogens.

Materials and methods

C. elegans strains and culture conditions

The following strains were obtained from the C. elegans Genetics Center (Minneapolis, MN, USA): N2 wild-type, DA531 eat-1(ad427), DA465 eat-2(ad465), NU3 dbl-1(nk3) and KU25 pmk-1(km25). BC14225 asp-5::GFP was obtained from the Genome BC C. elegans Gene Expression Consortium (Vancouver, British Columbia, Canada). The vha-12(n2915) mutant strain was a kind gift from Erik Jorgensen (University of Utah). The unc-32(e189) mutant and the transgenic strains containing full length GFP reporters, asp-3::GFP and asp-4::GFP, have been described previously [17,32]. We generated F44A2.3::GFP, vha-12(n2915);asp-4::GFP, pmk-1(km25);asp-4::GFP and dbl-1(nk3);asp-4::GFP using conventional genetic techniques. Growth and manipulation of C. elegans were as previously described [58,59].

Growing worms and infection

For microarray and qRT-PCR related experiments, eggs from N2 worms suspended in M9
buffer (3 g KH2PO4, 6 g Na2HPO4 and 5 g NaCl, dissolved in 1 mM MgSO4) were placed at 25°C and allowed to hatch in the absence of food. Aliquots of larvae
synchronized in this way were transferred after 16-20 h to NGM plates spread with
OP50 and cultivated at 25°C until the mid-L4 stage. Worms were then transferred to
assay plates. After 24 h at 25°C, the worms were collected, washed three times in
M9 buffer and total RNA extracted. Three independent infections were performed.

RNA sample preparation and microarrays

We added 1:10 volumes of Trizol (Invitrogen; Carlsbad, California, USA) to worms and
total RNA extraction was carried out following the manufacturer's instructions. The
RNA was quantified using Eppendorf BioPhotometer and RNA quality ascertained via electrophoresis
with 1% non-dentauring, agarose gels. We have used microarrays with full genome coverage,
each having 23,232 features against 20,334 unique transcripts generated using probes
designed at the Genome Sequencing Center (StLouis, MO, USA). Oligo-probes were spotted
on UltraGAPS™ slides (Corning; Lowell, Massachusetts, USA) according to the manufacturer's
specifications at the Plateforme Transcriptome (Marseille-Nice genopole/CNRS/INRA;
Sophia Antipolis, France). There were 24 microarrays used in this study (4 groups
corresponding to the 4 pathogens with 6 microarrays per group). Experimental design
included duplicate competitive hybridizations in which the Cy3 and Cy5 labels were
swapped ('dye swap experiments'). Hybridization was done using an adapted version
of a protocol from the Genomics Core Laboratory at the JDavid Gladstone Institutes
(San Francisco, California, USA). Quenching and cleanup procedures were substituted
with that described in ProtocolQQ07 from the QIAGEN literature-database. In brief,
5 μg of RNA was converted to double-stranded cDNA with superscript II (Invitrogen)
using custom designed (dT)24-V primer (Sigma; St. Louis, Missouri, USA) and aminoallyl-dUTP (Sigma) nucleotide
analogs. The cDNA was then cleaned using Qiagen PCR purification kit (Qiagen; Venlo,
Limburg, Netherlands). Labeled cDNA probes were prepared via coupling to Cy3 or Cy5
mono-reactive dye packs (Amersham; Little Chalfont, Buckinghamshire, UK). After removal
of unincorporated dyes with a Qiagen PCR purification kit, two differentially labeled
probes were combined in a hybridization buffer containing 5× SSC, 0.2% SDS, 7 mM Tris-Cl,
0.2 mg/mL yeast t-RNA (Invitrogen), 0.2 mg/mL poly(A) DNA (Sigma). We used 55 μL of
this cocktail on each chip and incubated them at 45°C for 16 h in a water-bath. Following
hybridization, microarrays were processed according to recommended protocols for UltraGAPS™
slides. Microarrays were scanned on a SCANARRAY 4000 XL (Perkin Elmer; Waltham, Massachusetts,
USA) machine and image analysis was performed using QUANTARRAY version 2.1 (Perkin
Elmer). Spots with obvious blemishes were manually flagged and excluded from subsequent
analyses. Global array quality was kept consistent with normalization coefficients
for the fluorochrome channels controlled at <2, visualized using ArrayPlot version
3.0 [60].

Expression data pre-processing

We used 20,257 genes on the microarrays, having signal strengths twice that of background
and 'unflagged' data points in at least four out of six microarrays for each pathogen,
as the base group for all subsequent analyses. All primary microarray data have been
deposited at ArrayExpress, with accession number E-MEXP-766.

Data generated from the microarrays was normalized using 'Per Spot and Per Chip: Intensity
Dependent (Lowess) Normalization' in GeneSpring GX version 7.3 (Agilent Technologies;
Santa Clara, California, USA). Differentially regulated genes for individual datasets
(supplementary Table 1a in Additional data file 3) were arbitrarily identified using
the uppermost 18.75th percentile of a dataset initially formed from probes having
normalized, expression ratios (infected/control) >1.01 or <0.99 in at least 2/3 of
microarrays per 'dye-swap' group for a total of 4/6 microarrays per dataset.

Expression data analysis: exploratory analyses

Differentially regulated genes were used for exploratory analyses using clustering
and gene class testing techniques. Clustering was performed within GeneSpring GX version
7.3. Two cumulative groups comprosed of genes up- (n = 254) and down-regulated (n = 266) by at least 2 pathogens (supplementary Table 1c in Additional data file 3)
were separately clustered using Pearson correlation. Cluster merging was performed
using average linkage and bootstrapping done with 100 datasets.

Gene class testing was performed using Expression Analysis Systematic Explorer (EASE).
We annotated gene probes with Gene Ontology and euKaryotic Orthologous Group (KOG)
information available from WormBase WS160 [61]. We also added functional information obtained from numerous C. elegans-related experiments [8-11,24,37-39,62-75]. Each dataset corresponding to up- or down-regulated genes after infection with a
particular pathogen was individually tested. Over-represented gene classes were characterized
by EASE scores, which are sliding-scale, conservative adjustments of Fisher exact
probabilities (p < 0.05).

Expression data analysis: statistical testing

As alternatives to inference based on fold-change, two statistical approaches were
used to infer differentially regulated genes in our experiment. With the first, various
tools as implemented in the software package J/MAANOVA version 1.0a were used [76]. Briefly, raw data from 18 microarrays was normalized using 'Joint Lowess intensity-spatial
Lowess' transformation (6 each for E. carotovora, E. faecalis and P. luminescens). Normalized data were then analyzed with a variant of the 'mixed effects ANOVA model';
three components of variance were assumed in our model. Two fixed components were
'microarray-specific effect' (systematic variation on microarrays) and 'condition'
(infected or control). A random component, 'biological replicate' was used to address
random variation due to the three different sets of biological replicates used. Within
J/MAANOVA, a Fs-test [77] based on the James-Stein estimator [78] was used to identify genes differentially expressed between our two conditions of
interest. Robustness of ANOVA data was tested using a permutation test; means were
randomly permuted 500 times and test statistics were recalculated for differences
between the two conditions. Agreement between ANOVA and permutation test results would
indicate the robustness of the ANOVA model. False discovery rate (FDR) control adapted
from algorithms discussed by Benjamin and Hochberg [79] and Storey [80] was applied to provide 95% confidence.

The second analysis was performed using tools within BRB-ArrayTools version 3.4.1
[81]. Raw data from 18 microarrays (6 each for E. carotovora, E. faecalis and P. luminescens) were transformed using 'Lowess intensity dependent normalization' to adjust for
differences in labeling intensities of the Cy3 and Cy5 dyes. The adjusting factor
varied over intensity levels [82]. Data were partitioned into two classes, one for infected animals and the other for
control. Using the 'class comparison' multivariate permutation test and averaging
dye-swapped experiments, we identified genes that were differentially expressed between
'infected' and 'control'. We used this test with 90% confidence so that the FDR was
less than 10%. The FDR is the proportion of the list of genes claimed to be differentially
expressed that are false positives. The test statistics used were random variance
t-statistics for each gene [83]. Although t-statistics were used, the multivariate permutation test is non-parametric
and does not require an assumption of Gaussian distributions.

qRT-PCR measurements

cDNA was prepared from each sample using the following reverse transcription protocol.
Total RNA (2.5 μg) was mixed with 2.5 μg (dT)24-V primer, incubated at 70°C for 10 minutes, then cooled on ice for 5 minutes. This
was mixed into a cocktail, 0.5 mM dNTPs (Invitrogen), 1× First Strand Buffer (Invitrogen),
10 mM DTT (Invitrogen), 50 u RNasin (Promega; Madison, Wisconsin, USA) and 400 u SuperScript™
II (Invitrogen). Reverse transcription was carried out at 42°C for 1 h, the reaction
terminated at 65°C for 10 minutes. All qRT-PCRs were carried out using SYBR® PCR Master Mix (Applied Biosystems; Foster City, California, USA) according to manufacturer's
specifications and analyzed on a GeneAmp® 5700 (Perkin Elmer). Expression data were collected as Ct values, where Ct is equal
to the number of PCR cycles required to amplify a given gene from a cDNA population.
Under 'infected' conditions, C. elegans grown on E. coli OP50 were exposed to pathogenic bacteria at the late-L4 stage, whereas 'control' animals
were continuously cultured on E. coli OP50. Changes in gene expression for both infected and control animals were initially
measured as ΔCt values and subsequently normalized against a control-gene: Pan-actin
(left primer ccatcatgaagtgcgacattg, right primer catggttgatggggcaagag). For example,
to measure up-regulation in infected animals (ΔCt(infected-control)), Ct values collected
from control cDNA were subtracted from Ct values collected from infected cDNA. Thus,
ΔCt(infected-control) = Ct(infected) - Ct(control). For all primer sets used in this
study (see supplementary Table 5 in Additional data file 3), DNA amplification was
linear in the relevant range of measurement; consequently, ΔCt = 1 corresponded to
an approximate two-fold change in DNA concentration. Finally, fold change values were
estimated by:

Fold change = ΔCt, where ΔCt is change in cycle number

Reporter constructs/promoter GFP constructs

Expression patterns for several genes were examined via the use of promoter GFP constructs.
Where transgenic, GFP-expressing strains were not already available, new strains were
created as previously described [84]. Briefly, promoter fragments fused to GFP amplified from plasmid pPD95.75 were microinjected
into N2 animals. PCR products were injected along with the pcol-12::dsRED selection marker [85]. Transformed animals were subsequently identified by the presence of dsRED expression.
All qualitative experiments with GFP-expressing strains were done using 40-100 animals
transferred onto pathogen assay plates. Relevant information for primers and transgenic
strains can be found in supplementary Table 5 in Additional data file 3.

Pathogen colonization

Infected worms were assayed using a slight modification of a previously described
procedure [86]. Fifty worms in a 15 ml tube were washed five times with 7 ml of M9 buffer containing
1 mM sodium azide. Worms were anesthetized by the effects of sodium azide during these
washes. Consequently, loss of bacteria from within the animals was minimized whilst
unwanted bacteria on external surfaces were removed. All subsequent steps remained
unchanged.

Survival assays

Synchronous populations of worms were established by allowing 20 adult hermaphrodites
to lay eggs for a limited time interval (4-5 h) on NGM plates seeded with E. coli OP50. Progeny were grown at 20°C, through the L4 larval stage and then transferred
to fresh plates with groups of 10-20 worms per plate for a total of 100-150 individuals
per experiment. Survival assays were performed at 20°C on NGM plates containing either
a pathogen or E. coli OP50. The first day of adulthood was defined as t = 0. Animals were transferred to
fresh plates every two to four days thereafter and were examined daily for touch-provoked
movement and pharyngeal pumping, until death occurred. We used the Prism software
package (GraphPad Software Inc.; San Diego, CA, USA) to carry out statistical analyses
and the log-rank (Mantel-Cox) test was used to evaluate differences between different
conditions. Worms that died due to internally hatched eggs, an extruded gonad or prolonged
periods spent at the edges of plates, were censored as described within Prism.

Acknowledgements

We are grateful to L Sofer and F Hilliou (UMR1112 INRA/University Nice Sophia Antipolis)
for expert technical assistance and advice. Microarray experiments were carried out
using the facilities of the Marseille-Nice Genopole®. Statistical analyses were performed with the help of H Schulenburg and E Remy, using
BRB ArrayTools developed by Dr R Simon, A P Lam and J/MAANOVA developed by Dr H Wu,
L Wu. We thank T Lamitina for communication of unpublished results, CCouillault and
OZugasti for performing microinjections, S Jarriault and BPodbilewicz for cell identification,
PGolstein, HSchulenburg, K Ziegler and all members of the Ewbank lab for discussion
and critical reading of the manuscript. Some nematode strains used in this work were
provided by the Caenorhabditis Genetics Center, which is funded by the NIH National Center for Research Resources
(NCRR). This work was supported by a grant from Sanofi-Aventis France (SanofiAventis
Group) and Bayer Pharma as part of a multi-organism call for proposals, institutional
grants from INSERM and the CNRS, a CNRS Puces à ADN grant, and the RNG.